Brain Computer Interface (BCI) machine in this project is developed with Rehabilitation hand to enhance and amplify the motor function feedback for the subject to strengthen then connection between the muscle activation and brain activities in order to recover their paralyzed motor function. In this paper, the highlight will be on Reality and Virtual Control analysis of the BCI ma-chine accuracy in control for 10 different subjects. The classifiers LDA and ESD will be used in the BCI machine. The EEG coverage area is F7, F8, FC5, FC6, F3 and F4. The aim of the project is to have a system that is controlled by Electroencephalogram (EEG) BCI that improves Neuroplasticity Brain activation for Rehabilitation of Stroke Patient on Finger-hand paresis. The BCI analysis is focused on temporal information features extractions. The outcome of the project achieved overall control accuracy for manual control is 40% and for auto control is 30% in online BCI, which is promising.
机构:
Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)
Ang, Kai Keng
;
Guan, Cuntai
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机构:
Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)
机构:
Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)
Ang, Kai Keng
;
Guan, Cuntai
论文数: 0引用数: 0
h-index: 0
机构:
Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)Institute for Infocomm and Research, Agency of Science, Technology and Research (A STAR)